Delft University of Technology
FACULTY MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department Maritime and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl
Specialization: Production Engineering and Logistics
Report number: 2014.TEL.7843
Title:
Adding a value chain perspective
to improve quality in material
flow within VDL ETG Eindhoven
product group Medical Systems
Author:
W. Boersma
VDL Enabling Technologies Group
Title (in Dutch): Toevoegen van een ketenperspectief om kwaliteit te verbeteren in de materiaalstroom binnen VDL ETG Eindhoven product groep Medical Systems
Assignment: Masters thesis
Confidential: Yes (until March 13, 2019)
Initiator (university): dr. W.W.A. Beelaerts van Blokland Initiator (company): ir. J. Zwiep (VDL ETG Eindhoven) Supervisor: prof.dr.ir. G. Lodewijks
Date: March 13, 2014
This report consists of 84 pages and 12 appendices. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all
T
U
Delft
FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERINGDelft University of Technology Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl Student: Supervisor (TUD): Supervisor (Company):
W. Boersma Assignment type: Master thesis dr. W.W.A. Beelaerts Creditpoints (EC): 35
van Blokland (TU Delft)
ir. J. Zwiep (Company) Specialization: Report number: Confidential: PEL 2014.TEL7843 Yes until March 13, 2019
Subject: How to Optimize Assembly Processes for Capital Goods Industry
VDL Enabling Technologies Group Eindhoven is subcontractor for Philips Medical Systems and assembles subassemblies for Philips CT scanners. The Fira is a ceiling system that contributes to a hybrid operating theatre and the Miura is a combination of a c-arc geometry and corresponding suspension. Both are assembled at a hired production facility. The preceding processes (e.g. welding, cutting and grinding) take place in a jobshop environment. VDL ETG Eindhoven normally assembles high-tech equipment in cleanrooms. The conditions for assembly of CT scanners are less complex and can take place in ordinary atmospheric conditions.
Prior research can be found in similar case studies. Lean Manufacturing has proven to have tremendous impact on the flexibility, controllability and cost of production processes.
The focus of this research lies on the material flow to the assembly department. Quality issues in the material flow disturb the assembly process. The costs and effects of these disruptions are however not clear. The profit margin within medical products is small and therefore there is need for a supply of material with minimal effects of disruptions in order to minimize waste.
The report should comoly with the guidelines of the section. Details can be found on the website.
The professor ai/d supervisor.
Preface
Starting the research assessment I was enthusiastic. The goal was clear: optimize the assembly process for the product group Medical Systems within VDL ETG Eindhoven. This wasn’t easy, noticing the shortages and quality issues in the supply of material. A couple of months later, the goal changed to ‘improve the supply of material’. Was this the right goal? And what is the problem? In classes we learned that ‘the right goal’ is needed to solve the right problem. What was the problem I would solve?
For me it was difficult to define the right problem. Maybe because all problems could be putted in perspective and in the end all problems don’t exist anymore. The question rises ‘What is a problem?’ and I found the definition to be: the difference between current situation and the required or desired situation. From my point of view the desired situation is rather subjective. Now, at the end of the research, I would say that however it is subjective; the desired situation can be defined in a way, by using theoretical background (i.e. there is a desired theoretic ideal). And that is what I tried in this research, to depict the difference between the current situation and the ideal situation following theory and suggest ideas for improvement. This made me thought it was a practice-oriented case study. Later I understand that scientific research should also add something to current theories and that I therefore was executing a theory-building case study (Dul & Hak, 2008). By relating the bullwhip effect to continuous improvement and to come up with a continuous improvement process model, I hope I did.
To work in such a large organization made me feel drowned so now and then, but I survived. And however the final result could have been better (it could always been better isn’t?), the process has been adventurous and educational. Especially thanks to the support of Wouter Beelaerts and his help to find the right focus and give the research its scientific value. And thanks to professor Lodewijks for his constructive feedback during meetings. Also thanks to the supervisor of the company, Jeroen Zwiep, for his time and supervision.
I would thank my God for His loving kindness and grace. And I would thank my uncle, aunt and cousin for their hospitality and letting me stay with them as long as needed and I am grateful to Elise for her support. My friends where very generous to share their house with me for the weekends and I am grateful to that. So many people to thank and of course I forgot someone. Nevertheless, thanks to all of them.
Eindhoven, 14 February 2014
Summary
VDL ETG Eindhoven is a ‘tier-1’ supplier for Philips Medical Systems (PMS) and delivers systems that are part of CT scanners. The Fira is a ceiling system that contributes to a hybrid operating theatre and contains two rails and a carriage. The Miura is a combination of a c-arc geometry and corresponding suspension, which contributes to a mobile CT scanner. These systems are assembled at the assembly department that is distanced from the main production facility and head office of VDL ETG Eindhoven. All material is transported from the warehouse to the assembly department.
The considered assembly department experiences disturbances in the material supply due to quality issues. The profit margin within medical products is however small and therefore there is need for an excellent supply of material, for it is expected that this reduce total cost. This research focuses on the quality of supplied material to the final assembly. The main research question is “How to improve the flow of material through the value chain from a quality perspective?”
Answer is found using the DMAIC improvement cycle, which is a framework for improvement projects. The Delft Systems Approach and lean theory is used as theoretical background from which
improvements are suggested. Reducing the amount of process steps results in reduction of
complexity, which results in reduced (quality) costs. Evidence for the bullwhip effect is searched for, because this is theoretical correlated to continuous improvement.
PMS demands a high standard on visual quality in case Miura and the current system is only able to meet this high standard with an internal rejection rate of 10,8% of handgrips at the assembly
department for the Miura c-arc Geometry. The costs are estimated to be at least €10.000,- in the year 2013, from which €7.500 (75%) are related to the process (i.e. extra material handling and
registration). The root cause is found to be a different interpretation of quality standards between quality inspection points (i.e. painter, production, assembly and PMS). By implementing a control loop between PMS and the painter, the interpretation of the quality standard is synchronized. The proposed loop gives direct feedback to the system that can influence paint quality (i.e. painter). Besides, other quality inspections in the value chain are eliminated. In the end it leads to an improvement of the paint process (i.e. less rejections at painter), which lower the overall costs in the value chain.
In case Fira the complaints registration program shows that on average 8,8% of the delivered plates are damaged when reaching the assembly department. The costs of this issue is approximately €4.000,- in the year 2013, from which €2.800,- (70%) are related to the process. This research postulates that the root cause is related to material handling. Eliminating material handling processes reduces risks and also makes finding the root cause easier. The amount of process steps in the warehouse is reduced from seven to five, which shows that complexity reduction in the value chain results in added value. The complexity in the value chain could be further reduced by eliminating more process steps. Suggested is to deliver plates directly to the assembly line and introduce a kanban between supplier, painter and assembly. An ‘exchange’ package is used as kanban signal. The
amount of transactions in the warehouse is reduced from seven to zero. Added value can be found in lower total costs, the reduction of damage risks, planning and control.
This research found variation in forecast information for both cases, Miura and Fira. The bullwhip effect theory states that this causes a high WIP and inventory. Especially the Miura assembly process contains WIP of twice the reasonable amount. The order lead-time, which is also related to the bullwhip effect, is found to be approximately nine to ten times the expected value for the Fira system; and three to four times for the Miura.
From the analysis of quality issues is concluded that the current value chain lacks continuous improvement (CI). Lean theory also postulates that high WIP hinders CI, which therefore can be correlated to variation in forecast information. The root cause is found in a missing CI process. This research postulates a new model wherein DSA and the DMAIC improvement cycle are combined in order to introduce continuous improvement from the value chain perspective. The value chain
perspective is postulated as essential for continuous improvement. Better registration of quality issues is however needed as input for CI. Another recommendation is to formalize communication from the assembly floor. This could be enhanced by a continuous improvement message board.
This research postulates that process KPIs are needed in addition to the current results KPIs in order to enhance value chain perspective. Three KPIs are suggested: amount of internal complaints in REM, throughput time of suggested improvements (via CI message board) and the amount of correcting activities.
The quality of material flow through the value chain could be improved by enhancing a value chain perspective. Three main improvements are suggested: direct control loop for paint quality in case Miura, kanban system for plate material between supplier, painter and assembly in case Fira; and a CI process model for both cases. These improvements reduce complexity c.q. the amount of process steps, which lead to lower costs and a higher reliability of the material flow.
Further research can be done in quantifying the effects that an unreliable supply of material has on the assembly process. Also research is recommended on finding other key performance indicators. This research is limited and suggests KPIs that enhance continuous quality improvement. And all research that focuses on complexity reduction is recommended, such as the introduction of more kanban systems in the value chain in order to reduce complexity even further and improve processes.
Summary (in Dutch)
VDL ETG Eindhoven is een ‘tier-1’ toeleverancier voor Philips Medical Systems (PMS) en levert systemen die onderdeel vormen van CT scanners. De Fira is een plafond systeem dat een hybride operatiekamer mogelijk maakt en bestaat uit twee rails en een rolkast (carriage). De Miura is een combinatie van een c-boog en een bijbehorende ophanging (suspension), welke bij een mobiele CT scanner horen. Deze systemen worden geassembleerd in een assemblage locatie op afstand en al het materiaal wordt getransporteerd vanuit het magazijn hiernaartoe.
De assemblage heeft last van verstoringen in de toevoer van materiaal vanwege kwaliteitsproblemen. De winstmarge binnen de medische producten is klein en daarom is een uitstekende toelevering van belang, omdat dit naar verwachting de kosten reduceert. Dit onderzoek legt zich toe op de kwaliteit van de toeleveringen aan assemblage. De onderzoeksvraag is “Hoe kan de materiaalstroom worden verbeterd door de keten vanuit kwaliteitsperspectief?”
Deze vraag is beantwoord aan de hand van de DMAIC verbeter cyclus dat structuur geeft voor continue verbetering. De Delftse systeemkunde en lean theorie zijn gebruikt als theoretische
achtergrond waarmee verbeteringen zijn voorgesteld. De onderliggende theorie voor dit onderzoek is dat de vermindering van complexiteit resulteert in minder proces stappen, wat resulteert in minder (kwaliteits)kosten. En bewijs is gezocht voor het opslingereffect in de keten, omdat dit continue verbetering theoretisch belemmert.
PMS heeft een hoge standaard voor de visuele kwaliteit in de Miura casus en het huidige systeem is niet in staat om deze te halen, zonder een intern afkeurpercentage van 10,8% op handgrepen binnen de assemblage voor de Miura c-boog. De kosten worden geschat op minstens €10.000,- voor 2013, waarvan €7.500,- (75%) gerelateerd is aan het proces (i.e. extra handelingen en registratie). De oorzaak blijkt een verschillende interpretatie van de kwaliteitsnormen tussen kwaliteitsinspecties (i.e. spuiterij, productie, assemblage en PMS). Door het implementeren van een regelkring tussen PMS en de spuiterij kan dit verschil weggenomen worden. De voorgestelde regelkring geeft directe
terugkoppeling aan degene die iets kan veranderen aan de kwaliteit (i.e. de spuiterij). Daarnaast worden andere inspecties op deze manier overbodig. Uiteindelijk moet het leiden tot een verbetering van het spuitproces (i.e. minder afkeur bij de spuiterij), zodat de totale kosten in de keten afnemen.
In de Fira casus laat het klachten registratie programma zien dat gemiddeld 8,8% van het
toegeleverde plaatmateriaal is beschadigd bij aankomst bij de assemblage. De kosten hiervan worden geschat op €4.000,- in 2013, waarvan €2.800,- (70%) gerelateerd is aan het proces. Dit onderzoek stelt dat de oorzaak is gerelateerd aan handelingen (m.n. intern transport). Het wegnemen van deze processtappen verlaagt het risico op beschadigingen en maakt het gemakkelijker om oorzaken te vinden. Het aantal processtappen in het magazijn is verminderd van zeven tot vijf. Wat laat zien dat het verminderen van complexiteit in de keten toegevoegde waarde oplevert. De complexiteit kan verder worden verminderd door nog meer processtappen te elimineren. Voorgesteld is om
plaatmateriaal direct te leveren aan de assemblage d.m.v. een kanban tussen toeleverancier, spuiterij en assemblage. Een ‘rouleer verpakking’ werkt in dit geval als een kanban signaal. Het aantal proces stappen in het magazijn wordt gereduceerd van zeven tot nul. De toegevoegde waarde is lagere kosten, minder risico op beschadigingen, minder planning en een lagere beheerslast.
Uit dit onderzoek blijkt dat er een variatie is in de prognose. Dit resulteert in veel onderhanden werk en voorraden (opslingereffect). Vooral het Miura assemblage proces heeft relatief veel onderhanden werk, welk ongeveer tweemaal de redelijke hoeveelheid werk onderhanden heeft. De order
doorlooptijd, welke ook gerelateerd is aan het opslingereffect, blijkt ongeveer negen tot tien keer zo lang te zijn dan verwacht bij het Fira systeem; en drie tot vier keer voor dat van het Miura systeem.
Uit de analyse van de kwaliteitsklachten is geconcludeerd dat de huidige keten trage continue verbetering kent. Lean theory stelt ook dat veel onderhanden werk continue verbetering tegenwerkt, waardoor dit gecorreleerd kan worden aan de variatie in de prognose. De oorzaak is dat er een proces voor continue verbetering ontbreekt. Dit onderzoek stelt een nieuw model voor waarin de Delftse systeemkunde en de DMAIC verbeter cyclus gecombineerd zijn om continue verbetering vanuit het ketenperspectief te introduceren. Betere registratie van kwaliteitsklachten is nodig als invoer voor dit proces. Andere aanbeveling is om de communicatie vanuit de werkvloer te formaliseren. Dit kan gedaan worden door een continu verbeter bord.
Dit onderzoek stelt dat proces prestatie indicatoren benodigd zijn als aanvulling op de huidige resultaatgerichte indicatoren, om zodoende het ketenperspectief te ondersteunen. Drie indicatoren (KPI’s) zijn voorgesteld: aantal interne klachten in REM, doorlooptijd van voorgestelde verbeterideeën (via verbeterbord) en het aantal correctieve acties op materiaal.
De kwaliteit van de materiaalstroom door de keten kan verbeterd worden door meer vanuit de keten te kijken. Drie verbeteringen zijn voorgesteld: directe regelkring voor lakkwaliteit in de Miura casus, kanban systeem voor plaatmateriaal tussen toeleverancier, spuiterij en assemblage in de Fira casus; en een ‘continue verbetering proces model’ voor beide. Deze verbeteringen reduceren complexiteit c.q. het aantal proces stappen, wat leidt tot lagere kosten en een hogere betrouwbaarheid van de materiaalstroom.
Verder onderzoek kan gedaan worden in het kwantificeren van de effecten op het assemblage proces dat een onbetrouwbare toelevering heeft. Ook onderzoek wordt aanbevolen om meer KPI’s vast te stellen. Dit onderzoek is beperkt and suggereert KPI’s die zich richten op continue
kwaliteitsverbetering. Daarnaast wordt al het onderzoek dat zich richt op complexiteitsreductie
aanbevolen, zoals de introductie van meer kanban systemen in de keten; zodat complexiteit nog meer verminderd wordt en processen nog meer verbeterd.
List of abbreviations
CI Continuous Improvement
CLIP Customer Line Item Performance CODP Customer Order Decoupling Point DMAIC Define Measure Analyze Improve Control DSA Delft Systems Approach
ETG Enabling Technologies Group
iQBS Intelligence Cubes (Excel based Business Intelligence solution) JIT Just-in-Time
LSL Lower Stock Level
NPI New Product Introduction OEM Original Equipment Manufacturer PDCA Plan Do Check Act
PMS Philips Medical Systems
QLTC Quality, Logistics, Time and Costs REM Complaints registration program
SMOI Supplier Managed and Owned Inventory TCT Transaction Cost Theory
USL Upper Stock Level VDL Van der Leegte
VMOI Vendor Managed and Owned Inventory VSM Value Stream Mapping
Contents
Preface ... 1
Summary ... 2
Summary (in Dutch) ... 4
List of abbreviations ... 7
Contents ... 8
1. Introduction ... 10
2. Methodology ... 12
2.1.
DMAIC improvement cycle ... 12
2.1.1.
Define ... 12
2.1.2.
Measure ... 12
2.1.3.
Analyze ... 12
2.1.4.
Improve ... 13
2.1.5.
Control ... 13
2.2.
Delft Systems Approach ... 13
2.2.1.
Theory and practice ... 14
2.2.2.
Systems concept ... 14
2.3.
Lean Manufacturing ... 15
2.3.1.
Principles of lean ... 15
2.3.2.
Waste ... 15
2.3.3.
Flow ... 16
2.3.4.
Customer order decoupling point ... 16
2.3.5.
Kanban ... 16
2.3.6.
Complexity ... 17
2.3.7.
Transaction costs ... 18
2.4.
Key Performance Indicators ... 19
2.5.
Bullwhip effect ... 20
2.6.
Framework ... 21
3. Measure and Analyse – Ist Situation ... 24
3.1.
Two case studies ... 24
3.1.1.
Differences ... 24
3.1.2.
Built-to-print versus built-to-spec ... 25
3.1.3.
Release for volume ... 25
3.2.
Shared processes ... 26
3.2.1.
Order process ... 26
3.2.2.
Material logistics process ... 29
3.2.3.
Quality process ... 31
3.2.4.
Information process ... 34
3.3.
Case Miura ... 36
3.3.1.
Customer need versus forecast information ... 36
3.3.2.
Work in process and lead-time ... 38
3.3.3.
Miura assembling process ... 40
3.3.4.
Production process c-arc geometry ... 42
3.3.5.
Quantifying quality issues Miura ... 43
3.3.6.
Costs of quality issues ... 47
3.3.8.
Conclusion case Miura ... 50
3.4.
Case Fira ... 51
3.4.1.
Customer need versus forecast information... 51
3.4.2.
Work in process and lead-time ... 53
3.4.3.
Fira assembling process ... 54
3.4.4.
Production process Carriage ... 56
3.4.5.
Quantifying quality issues Fira... 56
3.4.6.
Costs of quality issues ... 60
3.4.7.
Root causes of quality problems ... 61
3.4.8.
Conclusion case Fira ... 64
3.5.
Conclusion ... 64
4. Improve and Control – Soll Situation ... 66
4.1.
Case Miura ... 66
4.1.1.
Solution ... 66
4.1.2.
Validation reduction of rejected handgrips at assembly ... 68
4.2.
Case Fira ... 68
4.2.1.
Solution ... 69
4.2.2.
Validation reduction of damaged plates at assembly ... 74
4.3.
Continuous improvement ... 75
4.3.1.
Solution ... 75
4.3.2.
Key Performance Indicators ... 78
4.3.3.
Validation continuous improvement ... 80
5. Conclusions ... 81
6. Discussion and Recommendations ... 82
References ... 84
Appendix A: Scientific Research Paper ... 85
Appendix B: Total score by customer ... 91
Appendix C: Demand versus forecast Suspension ... 92
Appendix D: Demand versus forecast Geometry ... 93
Appendix E: Demand versus forecast Carriage ... 94
Appendix F: Demand versus forecast Rails ... 95
Appendix G: CLIP and Backlog Purchasing ... 96
Appendix H: CLIP and Backlog Parts ... 97
Appendix I: Forecast Philips Medical Systems ... 98
Appendix J: Cost calculation ... 99
Appendix K: Ishikawa-diagrams ... 102
1. Introduction
Van der Leegte Groep (VDL Groep) is an international industrial company focused on the
development, production and sale of semi-finished products, busses and coaches and other finished products. In the near future also cars will be produced. It is a conglomerate of flexible, independent companies, each with its own specialty. Since its founding in 1953, the VDL Groep has grown to include 82 operating companies, spread over 18 countries, with more than 8,700 employees. The head office is situated in Eindhoven.
One of the companies is VDL Enabling Technologies Group (VDL ETG). This company has four production locations; in Eindhoven, Almelo, Singapore and Suzhou (China). It is a tier-1 contract manufacturing partner. Customers are leading high-tech Original Equipment Manufacturing (OEM) companies and users of advanced production lines. The turnover of VDL ETG Eindhoven in the semiconductor sector is about 80% of the total turnover.
VDL ETG Eindhoven is among others, subcontractor for Philips Medical Systems (PMS) and assembles subassemblies for Philips CT scanners. The Fira is a ceiling system that contributes to a hybrid operating theatre (Figure 2) and the Miura is a combination of a c-arc geometry and corresponding suspension, used for the Philips Veradius mobile CT scanner (Figure 1). Both are assembled at a hired assembling facility (10 minutes drive from main location). The preceding processes (e.g. welding, cutting and grinding) take place in a job shop environment. VDL ETG Eindhoven normally assembles high-tech equipment in clean rooms. The assembly of CT scanners take place in ordinary atmospheric conditions.
Figure 1: Philips Veriadius mobile CT scanner (Miura part: c-arc + suspension, without electronics)
Figure 2: Philips hybrid operating theatre (Fira: hybrid ceiling carriage + rails)
The considered assembly department experiences disturbances in the material supply due to quality issues. The profit margin within medical products is however small and therefore there is need for an excellent supply of material, for it is expected that this reduces total cost. This research focuses on the quality of supplied material to the final assembly. The main research question is “How to improve the flow of material through the value chain from a quality perspective?”
The objective of this research is to find an answer to the main research question using theoretical background from the Delft Systems Approach and lean manufacturing theory. The research is executed following the DMAIC improvement cycle. This method is described in 2.1 DMAIC improvement cycle. Chapter 2 gives an overview of the used methods, theory and literature. In chapter 3 the current situation is discussed. It contains measurements, an analysis and conclusions for two case studies, Miura and Fira. For each case an improvement is suggested, which are discussed in chapter 4. The report ends with conclusions (chapter 5) and discussions and recommendations in chapter 6.
2. Methodology
This chapter contains the methods and theories applied in this research. The framework for the research is the DMAIC improvement cycle. The D stands for ‘define’, which incorporates, among others, this chapter. Admitted to this chapter are the theories from the Delft Systems Approach, lean manufacturing, key performance indicators and the bullwhip effect.
2.1.
DMAIC improvement cycle
For improving, optimizing and stabilizing production processes often the DMAIC improvement cycle is used. It is also used for process redesign. The abbreviation DMAIC stands for define, measure, analyze, improve and control (DMAIC: The 5 Phases of Lean Six Sigma, 2012). This research turns this framework to account. The DMAIC improvement cycle is a core tool of Six Sigma, which focuses on improving quality of process output by identifying and removing root causes of defects and minimizing the variability in manufacturing processes as well in business processes. Below the different phases are described.
2.1.1. Define
In the define phase a clear definition of the research is formulated. This contains the field of research, information about the organization, a problem description, research question, scope and objective of the research. Also a research strategy is defined, including a timeline of the project. From the problem description and the research question also used literature, methods and theory is defined.
2.1.2. Measure
The purpose of the measure phase is to objectively establish the current process. This is the AS IS situation before improvement. In this phase a decision has to be made what should be measured and how. The following is contributed to the DMAIC cycle:
- Identification of the gap between the current performance and that what is required
- Data collection to create a process performance capability baseline - Assessing the right measurement system
- Establishing a process flow (at high level)
2.1.3. Analyze
The purpose of the analyze phase is to identify and select root causes for elimination. With the use of the Five Whys and an Ishikawa diagram the root causes can be found in a structured way. The root causes are the input for the improve phase. In fact, searched is for a relation between cause and effect. The measurements are therefore analyzed (e.g. with Pareto charts). Also detailed process schemes are used to relate causes and effects and pin-point what contributes to the occurrence of quality issues.
2.1.4. Improve
In the improvement phase new solutions have to be found by indentifying, validating and implementing. The improvements are creative and eliminate root causes found in the analyzing phase. In this phase brainstorming techniques can be used. However it is advised to focus on the easiest solutions and be creative. An implementation plan is mostly a part of this phase, just like the deployment of the improvement.
2.1.5. Control
After implementation, in the control phase, the new situation has to be
maintained. Therefore a control plan could be created. The improvements have to be monitored in order to control a sustainable solution. Updating documents, business processes and training records when the new situation requires these.
2.2.
Delft Systems Approach
Systems thinking, thinking in processes and system models emerged as a science in the 1940s and applied in companies in 1980s. It is found to be an effective way of thinking, because it fills a gap between theory and practice. The authors of ‘The Delft Systems Approach’ believe that there are four possible main reasons for this gap (Veeke, Ottjes, & Lodewijks, 2008).
First, there is a difference between finding a solution in theory and practice. Too many scientists presume that the manager attempts to find the absolute best solution to a problem. In practice, the interest level in doing this is not optimal. A manager is only marginally interested in various
sophisticated mathematical methods for partial problems, unless the advantage to be had is clearly demonstrable in advance.
Second, the researcher has not a time pressure in general. The manager instead has never enough time. Decisions have to be taken fast and the answers have to be simple.
Third, there is a fashion-conscious aspect to business management science. Lean production, business process redesign (BPR), Six Sigma etc. are techniques that focuses on one aspect of the whole
picture. This opinion is discussed, because lean production adds a value chain perspective and does not focus on one aspect for this reason. The DSA considers a system perspective and is missing a value chain perspective.
Fourth, much of the problems researched by scientists are not marked by managers as being the most important at the time. Managers are struggling with problems resulting from the increasing complexity and changing attitudes of individuals and society. New concepts have to be introduced rather than optimisations of existing processes. It is primarily about retaining or improving the effectiveness and flexibility of the organisation and far less about improving efficiency.
2.2.1. Theory and practice
The Delft Systems Approach (DSA) closes the gap between theory and practice from three different viewpoints. First, the DSA is an abstract and conceptual approach. Therefore the approach can be used multidisciplinary. It views the company as an integrated whole and can place into perspective and combine the contributions from the many other disciplines and therefore supports collaboration in a design project and provides a way to save the principal decisions and assumptions during a design project in a systematic way. However, the shortcoming of the DSA is that it misses a value chain approach.
Second, students are solution-oriented educated. Problems are well-defined and they are trained to find a solution to these problems. However in practice the problems are not well-defined at all. And translating situations to problems they recognize can lead to finding a correct solution to a problem that seems not the correct problem. This method supports the analysis of problems as well as the design of a solution.
Third, the systems approach primarily focuses first on the whole and then on the component parts. It provides a better insight into the flows through the company due to thinking in terms of processes and process functions. It closes therefore the gap between qualitative modelling and quantitative modelling.
2.2.2. Systems concept
The definition of a system is, depending on the researcher’s goal, a collection of elements that is discernible within the total reality. These discernible elements have mutual relationships with other elements from the total reality (Veeke, Ottjes, & Lodewijks, 2008).
The goal of a system is to fulfil functions in its environment. Figure 3 illustrates the concept of a function. Input is transformed into output to meet requirements that is expressed by its performance.
Figure 3: Simplest scheme of a function (Veeke, Ottjes, & Lodewijks, 2008)
A function is less time-dependent than a task, because tasks have to be done within a time period or before an expiration date. For example a train has the function to ‘transport’. This is what a train is made for. A train that cannot fulfil this function cannot be seen any longer as a train. A task could be to ‘stop at platform B’. To fulfil the function it has to do certain tasks. It is important to remember that
2.3.
Lean Manufacturing
Within business the lean approach is much applied in the last century for it has proven tremendous impact in production processes. Central in lean manufacturing is the continuous improvement of processes and the development of people in order to generate more customer value. The main target of lean manufacturing is to eliminate waste in order to improve flow of material in the value chain. It turns out that the result is more flexibility, lower value of the material flow and a faster response to customer requirements. By improving quality the throughput is shorted and the operational costs are decreased.
2.3.1. Principles of lean
Five basic principles of lean are defined as follows (Womack & Jones, 1996): 1. Specify value
2. Identify the value stream 3. Make value flow
4. Let customers pull 5. Pursue perfection
These principles create a loop of continuous improvement. After ‘pursue perfection’ follows ‘specify value’ again as indicated by the arrow. First it must be specified where the customer is willing to pay for, because this is the value what need to be added by the process. Second the value stream must be identified, that is, all value-creating steps in sequence. Then all steps need to be tight sequenced in order that the material will flow through this chain of steps. Create only value when the customer asks for it. Finally this process is continued until perfection is reach without any waste in the value stream and maximum customer value is created.
2.3.2. Waste
Eliminating waste is the main objective within lean manufacturing. Waste is all the activities that do not add value to the final product. Value is any activity that transforms the product in a way the customer is willing to pay for. There are three kinds of activities: value-adding, non-value adding and necessary non value-adding. The non-value adding activities need to be eliminated.
The activity of assembling can be seen as value-adding, because customer is more willing to pay for an assembled product than for a product as separated parts. However IKEA and LEGO do not even assemble the final product. The customer is willing to pay for a wardrobe that is easy to transport and therefore not assembled at all. And the customer is willing to pay for a LEGO set and assemble the parts by himself. So waste is different for each product, customer and business. It depends on the basic question ‘what is value for the customer’? In general customers are not willing to pay for the following seven kinds of waste (TIMWOOD+):
1. Overproduction 2. Inventory
3. Defects/Rework 4. Transport 5. Motion 6. Waiting
7. Over processing
Others also include an eight loss (+): not using the capabilities and experience of employees.
2.3.3. Flow
All that lean manufacturing strives for is that all processes are linked to each other; from the final customer back to raw material. It is a smooth flow without detours and waiting times that generates the shortest lead time, highest quality, and lowest cost. It is a chain wherein each ascending process only produces what the next process needs when it needs it. Waste is in fact counteracting this flow of materials. For example, overproduction means that in a later stadium the products have to wait until the customer needs it. And inventory means that material is waiting and is inherently not ‘flowing’. Defects results in rework. Before rework the material has to wait, or the main production process has to stop, causing waiting materials. And even the transport causes material to ‘wait’ for further processes. All waste lead directly or indirectly to an interruption of the material flow. This concept is important to understand when using the principles of lean manufacturing.
2.3.4. Customer order decoupling point
Within a supply chain a lot of process steps are needed until the final product can be delivered to the end user. Before assembly, components have to be manufactured. And previously, materials have to be produced from raw materials achieved from mines. The total time exceeds many years and
customers do not want to wait that long. Therefore most processes are executed before knowing who the final customer is. The point in the supply chain where the product is labelled for a specific final customer is called the customer order decoupling point (CODP).
2.3.5. Kanban
To control the logistical chain in a ‘lean environment’, kanban is frequently used. It is a scheduling system for lean manufacturing. The kanban could be a three-bin system for example. One bin is at the factory floor, one is at the factory shop and one is at the supplier. The idea is generated by Toyota in the late 1940’s. In fact the system is like a supermarket where customers only pick the materials they need, knowing that the next time they come the stock is replenished.
When the bin at the factory floor is empty it is returned to the supplier and a new one is taken from the shelf in the factory shop. The supplier delivers a full one at the factory shop. The amount in the bin depends on the amount of material used and the supplying frequency.
In most cases the material that is supplied by kanban is of low value, because the system is
characterized by low monitoring and control. Therefore the costs of monitoring and control are less, but also more trust is needed in involved parties. However in theory kanban could be used for every material flow of every value. The supplier must be trustworthy and is given more responsibility.
Kanban is used where continuous flow does not extend upstream. There are often spots in the value stream where continuous flow is not possible and batching is necessary. There can be several reasons for this including:
- Some processes are designed to operate at very fast or slow cycle times and need to change over to serve multiple product families (e.g. stamping or injection moulding).
- Some processes, such as those at suppliers, are far away and shipping one piece at a time is not realistic.
- Some processes have too much lead time or are too unreliable to couple directly to other processes in a continuous flow.
2.3.6. Complexity
The complexity of a manufacturing system controlled by human will rise over time. Efstathiou gives two reasons for that: the combination of a more complex and uncontrollable external environment and the human tendency to establish informal customs and practices to solve problems. Complexity is costly and time-consuming. Efstathiou states however that some complexity is needed to be flexible (Efstathiou, 2002). Too much complexity leads to stress and an uncontrollable system for which it is difficult to focus on the added value for the customer. Energy dissipates on solving recurring
problems. Too few complexity leads to a system that is rigid and inflexible. Consequently it is not able to respond on fluctuations in customer demand.
In literature distinction is made between detail complexity and dynamic complexity. Detail complexity is defined as the distinct number of components or parts that make up a system, while the term dynamic complexity refers to the unpredictability of a system’s response to a given set of inputs, driven in part by the interconnectedness of the many parts that make up the system (Bozarth, Warsing, Flynn, & Flynn, 2009). Dynamic complexity is present when one action has one set of consequences locally and a very different set of consequences in another part of the system. Obvious interventions produce non-obvious consequences.
Lean manufacturing focuses on the elimination of waste. This results in the reduction of the ‘complexity of the system’, both detail as dynamic complexity. Duggan found a similar relation, that chaos reduction in manufacturing system results in shorter lead-time and vice versa (Duggan, 2002). In literature the supply chain complexity is conceptualized in three dimensions (Choi & Krause, 2005):
- the number of suppliers in the supply base
- the degree of differentiation among these suppliers - the level of inter-relationships among suppliers
A value chain contains multiple processes and each of them could be seen as a supplier of the next process and a customer of the preceding process. Dynamic complexity is increasing when the amount of supply processes increases. This phenomenon is also found in Transaction Cost Theory (TCT). Dynamic complexity can therefore be quantified by the amount of process steps with multiple suppliers.
2.3.7. Transaction costs
Transaction costs are inherent to complexity. Dahlman divides transaction costs in three broad categories: search and information costs, bargaining costs, and policing and enforcement costs (Dahlman, 1979). Transaction costs need to be added to the value of the purchased item in order to calculate the total cost related to economic exchange of material. Search and information costs are costs related to determining that the required good is available on the market, which has the lowest price, etc. Bargaining costs are the costs required to come to an acceptable agreement with the other party to the transaction. Policing and enforcement costs are the costs of making sure the other party sticks to the terms of the contract, and taking appropriate (legal) action if not. Fundamentally, these three are one: resource losses incurred due to imperfect information (Dahlman, 1979).
Figure 4: Complexity versus costs Figure 5: Process steps versus costs
Williamson postulates that an understanding of transaction costs economizing is central to the study of organizations (Williamson, 1981). He states also that “A transaction occurs when a good or service is transferred across a technologically separable interface. One stage of activity terminates and another begins. With a well-working interface, as with a well-working machine, these transfers occur smoothly.” The transaction cost theory (TCT) by Williamson postulates that a transaction brings additional costs, costs of complexity (Choi & Krause, 2005). Inherent to costs are the costs of quality. Figure 4 shows an illustrative graph of the relation between complexity and costs, and inherent to that the relation between complexity and quality costs.
The amount of process steps is an indicator for the amount of transactions. Between each process step a transaction is made. During this research this is used as an indicator for the ‘level of complexity’ within a process. Within the DSA the process steps are visualized in a process scheme, which results in a clear vision of the reduction of process steps in the improvement phase; and therefore a clear representation of the reduced complexity. Figure 5 shows how the amount of process steps is related to quality cost.
Figure 6: Simplified LSSI value chain (Petrick, 2007)
Competition in the manufacturing industry changed from competing companies to competing supply chains or networks (Beelaerts van Blokland, Fiksinski, Amoa, Santema, Van Silfhout, & Maaskant, 2012). In Figure 6 the positioning of a tier-1 company in a supply chain is illustrated. The large-scale systems integrator (LSSI) focuses on market demand, research and development, sales and marketing and so on. The focal company connects the market to the tier-1 company. In the same way the tier-1 company connects the tier-2 to the focal company. The figure shows a typical value chain, from raw material to market. Reduction of complexity in the value chain and the processes within, leads to lower quality costs in the value chain.
2.4.
Key Performance Indicators
To establish an improved situation it is necessary to measure the current performance. “Performance measurement is a prerequisite for judging whether an operation is good, bad or indifferent.” (Slack, Chambers, & Johnston, 2007). Performance measurement gives Key Performance Indicators (KPIs). Slack defines five generic performance objectives: quality, speed, dependability (reliability), flexibility and cost.
The definition that is used by Slack for ‘performance’ is: the degree to which an operation fulfils the five performance objectives at any point in time, in order to satisfy its customers. From the DSA the performance is denoted by this formula:
𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 = 𝑒𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑛𝑒𝑠𝑠𝑎𝑐𝑡𝑢𝑎𝑙 × 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 (Veeke, Ottjes, & Lodewijks, 2008)
To prevent misinterpretation, the terms effectiveness and efficiency can be distincted by the reminder that effectiveness is determined as ‘doing the right thing’ and efficiency as ‘doing the things right’. The performance can be expressed in a measurable value such as time, speed and distance and can thus be measured by looking at tasks (e.g. the question ‘how long does it take to drive from A to B?’). Performance depends always on expectations and requirements, becayse “a performance measure means relatively little until it is compared against some kind of target.” (Slack, Chambers, & Johnston, 2007). Slack suggest four approaches to transform performance measures into performance
judgements: historically-based targets, strategic targets, external performance-based targets, and absolute performance targets.
Slack gives some typical partial measures of performance. For application in practice however, these are general and it lacks a method to achieve performance measures. Also the DSA gives only an abstract representation that limits practical implementation.
The ‘Organisational Cockpit’ is a concept for determining important KPIs (Kerklaan, 2009). The concept is based on a dashboard in an airplane. On this dashboard all the information the pilot needs for navigation, steering etc. is displayed. Kerklaan divides two kinds of information: navigation and system information. The first is all about ‘mission accomplishment’ and environment information, the second about the internal systems and available resources. Navigation information has a strong relation with effectiveness (e.g. the question ‘is the target achieved?’) and system information with efficiency (e.g. the question ‘how is the target achieved?’). Kerklaan postulates that both kind of information is needed for successfully flying an airplane.
The airplane is a metaphor for a company. To be successful a company needs performance indicators that indicate the results (navigation information) and that indicate process performance (system information).
2.5.
Bullwhip effect
Customer demand is rarely perfectly stable and therefore supply chains use forecasts to anticipate on this variance. By definition forecast information isn’t equal to actual customer demand and therefore safety stock is needed to prevent shortages of material. This causes a bullwhip effect in the supply chain. Jay Forrester described the bullwhip effect as a phenomenon in a forecast-driven supply chain (Forrester, 1961). An illustration can be found in Figure 7 below. The small variation in customer demands leads to tremendous variation upstream the supply chain. The bullwhip effect causes a high amount of work in process (WIP) and safety stocks (Lee, Padmanabhan, & Whang, 1997). In terms used in lean theory, the bullwhip effect leads to waste in the value chain.
Figure 7: Illustration of bullwhip effect Figure 8: Bullwhip effect on continuous improvement
In literature four major causes are found (Lee, Padmanabhan, & Whang, 1997): demand signal processing, rationing game, order batching and price variations. A vendor managed inventory (VMI), information sharing, and smoothing the flow of material reduces uncertainty, variability and lead time (Lee, Padmanabhan, & Whang, 1997). Other literature also concludes that VMI offers a significant opportunity to reduce the bullwhip effect in supply chains (Disney & Towill, 2003). Results of research indicate that eliminating the bullwhip effect can improve profitability dramatically (Metters, 1997).
So forecast errors, high WIP and long lead-times are indicators of the bullwhip effect. Because continuous improvement (CI) is opposed by high WIP and stock levels, and the bullwhip effect is causing these aspects; the bullwhip effect has to be eliminated in order to enhance CI. This relation is schematically illustrated in Figure 8. Literature found that information sharing is beneficial to
decreasing the bullwhip effect and inventories in supply chains (Kainumaa & Tawarab, 2006).
2.6.
Framework
From the methods and theory considered in this chapter a framework is defined. The DMAIC
improvement cycle is used as a framework for the research. This includes the final phase ‘control’ that assumes implementation is executed. To implement or not is however left for the company. The phase ‘control’ is thus not executed as intended (after implementation). This research considers a practical case and only suggests improvements for it. And it is also meant to be adding knowledge to current theoretical background.
Unreliable and variable forecast information is related to the bullwhip effect. The bullwhip effect causes high amount of WIP. The lean theory postulates that high WIP is related to ‘less continuous improvement’. This is illustrated in Figure 9. The water hides the rocks on the bottom of the sea and prevents collision of the ship. The inventory hides the problems (the rocks). For continuous
improvement, problems need to be solved. Therefore problems need to be identified. Lean postulates that the water level needs to decrease in order to solve problems and continuous improve processes.
Figure 9: Inventory hides problems and hinders continuous improvement
If existence of the bullwhip effect is proved (long lead-time, high WIP, safety stocks and unreliable forecast information), it is evidence for a slow continuous improvement process. The effect of a slow continuous improvement is that problems are not solved or the response to problems is slow. This includes quality issues and therefore continuous quality improvement. This should be visible in the amount of rejected items with one quality issue, related to time. In this case the figure of one sample period (e.g. one year) shows different incidents over time with a) the same value, b) increasing value, c) fluctuating value or d) a (too) slow decreasing value. In either case no quick response is identified, because this is reflected by an immediate decreasing value.
System thinking is effective for filling the gap between theory and practice. The DSA is a way to schematically present the current system and identify this gap in order to come to a future state representation. The steady-state model contains an executing process, a process control and a function control (see Figure 10). This model is limited and contains not a value chain perspective. The value chain perspective is needed to prevent sub optimization of processes within departments. Lean theory motivates to consider the value chain rather than one executing process.
Figure 10: Process control (Veeke, Ottjes, & Lodewijks, 2008)
The steady-state model in Figure 10 contains control functions on different levels. The objective of function control is to translate the requirements into measurable standards; and to evaluate results and translate this into performances. The objective of process control is to react to disturbances. The process control contains feedback and feed forward loops in order to do so. These control functions do not consider the question ‘how can the process be improved?’, but is focusing on ‘how can the process be adjusted in order to improve output?’. So it is not able to identify waste in the process, as the lean theory pursues; and therefore not able to improve processes from this perspective.
The lean theory considers eight wastes. Five of them are directly or indirectly related to quality: defects, overproduction, non-utilized talent, transportation and inventory. With these in mind quality risks can be deduced from process schemes from where a future state can be established. The DMAIC is a systematic stepwise approach and aims at quantifying these wastes in order to improve processes continuously. Quality is measured by complaint issues, WIP and throughput time is measured, even so the costs of unnecessary transportation and handling.
Lean theory strives for reducing waste. Waste and complexity are closely correlated and so lean manufacturing means reducing complexity. Complexity is found at different levels and is a very wide concept. This research focuses on the organizational and system level complexity. The internal
transactions in the value chain are not considered, because this adds to much detail that is considered as not necessary. By measuring the amount of process steps in the current process schemes,
complexity is quantified. Comparing the complexity in the future state with the current state shows a complexity reduction.
In Table 1 the methods and theory are related to the sections in this research report.
Table 1: Methods and theory per chapter
Section: Delft Systems Approach
Lean
Manufacturing
Complexity Bullw hip Effect Key Performance Indicators 3.2 x x x 3.2.1 x x 3.2.2 x x 3.2.3 x x 3.2.4 x 3.3 x x x x 3.3.1 x x 3.3.2 x x 3.3.3 x x 3.3.4 x x 3.3.5 3.3.6 3.3.7 3.4 x x x x 3.4.1 x x 3.4.2 x x 3.4.3 x x 3.4.4 x x 3.4.5 3.4.6 3.4.7 4.1 x x x 4.2 x x x 4.3 x x x
3. Measure and Analyse – Ist Situation
The current situation is established following the DMAIC improvement cycle. In this chapter both the measure and analysis phase (M and A in DMAIC) are described. Within the DSA the term ‘Ist situation’ is used. This chapter is about measuring and analysing the current situation as reference point for this research project and is used as a baseline for improvement. At the end the main conclusions are discussed in relation to the problem description and the research question. The main question that is answered is in this chapter is “How is the current material flow through the value chain from a quality perspective and what are the main issues and corresponding root causes?”.
3.1.
Two case studies
Within the VDL ETG division Medical Systems two Philips products are assembled; Miura and Fira. For this research this results in two case studies; case Miura and case Fira. The reason can be found in the differences between the products and their processes. On the other hand, in both cases they use shared processes such as order processing, material handling and quality control. These processes are described in the next paragraphs where after both case studies are elaborated separately.
3.1.1. Differences
The main differences in product characteristics between case Miura and case Fira are listed in Table 2 below. For a picture of the Fira and Miura product is referred to Figure 1 and Figure 2 in the
introduction chapter. A main difference is the visual quality the customer is asking for, ‘How does it look?’ The Fira is a technical product and is used in the ceiling of an operating theatre. The focus is on the technical quality (e.g. the question ‘Is the construction able to carry the weight of the CT
scanner?’). As a former machine manufacturing company and supplier of high-tech equipment, the employees are committed to manufacture high quality products. The Fira is mainly tested and judged on its function. For a medical system such as the Miura there is a very high norm for the visual quality. This means that every scratch and little damage in the varnish is a reason for rejection at the final check. Two aspects in Table 2 need further clarification; namely print’ versus ‘built-to-spec’ and to be released for volume or not. These aspects are elaborated in the next two
Table 2: Differences between Miura and Fira
Case Miura Case Fira
Built-to-print Built-to-spec
Not released for volume Released for volume
Output: ≈ 5 per week Output: ≈ 2 per week
Sales price: € 7.296 € 3.167 (geometry) € 4.129 (suspension) Sales price: € 32.105 € 19.516 (carriage) € 12.589 (rail set) Focus: visual quality Focus: functional quality Assembly time: 12,20 hours
4,10 hours (geometry) 8,10 hours (suspension)
Assembly time: 85,18 hours 55,40 hours (carriage) 29,78 hours (rail set) Number of parts: 229
56 different parts (geometry) 173 different parts (suspension)
Number of parts: 612 383 different parts (carriage) 229 different parts (rail set)
Aluminium Steel
3.1.2. Built-to-print versus built-to-spec
Built-to-print means that the customer delivers all drawings needed for the production of the product. The customer decides how the product is made and which procedures have to be used. Even suppliers are mostly chosen by the customer (in this case PMS). Built-to-spec means that the customer asks for a product that meets certain specifications. The supplier is usually responsible for the design,
procedures and drawings for the product in this case.
3.1.3. Release for volume
Before the product can be manufactured in volume it starts with a project. The department ‘New Product Introduction’ (NPI) is responsible for the ‘release for volume’ (R4V). The ‘release for volume checklist’ consist approximately 100 checks that must be completed before the product can be released for volume. When signing for the R4V milestone, the production department accepts that all aspects in the R4V checklist are fulfilled and that the product is ready to be produced with regular production procedures and regular production staff. The checks are basically answering the question ‘how do we guarantee that the products we deliver satisfy customer needs?’
3.2.
Shared processes
In this paragraph the shared processes are elaborated. This is done by using the Delft Systems Approach (DSA). In fact three sequencing processes can be deduced when studying the material flow within VDL ETG; 1) production at the main location, 2) warehousing and transport, and 3) assembling at the separated location. The material flow is initiated by the order process, which is therefore first described in the next subparagraph.
3.2.1. Order process
General speaking, within production facilities the customer need is translated into orders. The order is checked and if the company is able to execute this order, a production order is send to the production department. An invoice is sent to the customer and after payment the product is shipped. This ‘old-fashioned way of producing’ had to move over for a modern way of fulfilling customer needs. That is by the use of a vendor managed and owned inventory (VMOI), which implicates that the vendor is responsible for keeping the inventory between a lower stock level (LSL) and an upper stock level (USL) and is (financial) responsible for the inventory. This inventory is located at the customer, who is able to pick the item when needed and have it just-in-time (JIT) at his own assembly line.
The customer order decoupling point (CODP) is situated in the VMOI, because PMS assembles products to customer order while the products in the VMOI are not. Based on forecast information VDL ETG pushes products in the inventory and customer orders pull products through the final assembly at PMS. The CODP is the connection between push and pull and therefore also called push-pull point.
The practical implication is that VDL ETG pushes products to the VMOI. This conflicts with the fourth lean principle ‘let customers pull’. The planning department focuses on the LSL and the USL in the VMOI in order to meet the contract. However, because demands vary and the supply of material is not very flexible or even unreliable, the planners use the VMOI as safety stock and act upon the USL (‘better safe than sorry’). The result is that an imaginary ‘pull’ is created through the supply chain without actual ‘customer demand’. This aspect is important to understand, because it impacts the material flow through the value chain.
Another implication of the VMOI based agreement is that PMS does not order products, but
communicates needs by forecast information. But VDL ETG is driven by orders and can only produce based on an order. This discrepancy leads to a disconnection. Therefore forecast information need to be translated to production orders by the planning department. This aspect adds complexity to the system, because it adds extra (non-value adding) steps to the process. This process can be seen in Figure 11 (for an enlarged version see Appendix L: Enlarged copies of process schemes).
Figure 11: Schematic order process (DSA)
Forecast information is entering the process (input). The output is a) a delivered order and b) an invoice for the administration department. From the ‘waiting production orders’ an arrow is crossing the system border. Production orders are executed in the warehouse and assembly department (order picking and assembling). The main cause for this apparent complicated process is the (necessary) use of an ERP system.
3.2.1.1. BaaN ERP
The enterprise resource planning (ERP) system is made for the planning and traceability of customer orders. The input is a new customer order and the output is a delivered order (belonging to a finished product). The ERP system of VDL ETG, called ‘BaaN’, is used to schedule all customer orders in the daily and weekly capacity.
The order manager is able to see a forecast of 12 months online at the ‘Philips portal’. The data is copied in the BaaN ERP system. The integral planner is responsible for the production schedule and is using the forecast, LSL and USL as input information. He decides if the demand (forecast) of the customer (PMS) is feasible and takes care of the needed actions. He makes the main production schedule (MPS) from where advices are generated for purchase and production orders. When the product is ready the invoice is generated and the customer pays.
The difficulty in the current situation is that the forecast must be transformed into a customer order; and that after the delivery no invoice could be generated, because the product is not yet sold. This results in more steps that need to be done manual. After the item is picked from the shelf at PMS, PMS sends a confirmation as a so-called ‘credit invoice’. The order manager is then able to generate manually the invoice in the BaaN ERP system for the administration department and PMS pays automatically (does not need to receive an invoice).
The amount of type of products that is delivered via a VMOI in the current state is seven (see
Appendix I: Forecast Philips Medical Systems). And from these products a total of 972 products (forecast of week 29 ’13 to week 28 ’14) have to be delivered in the next year. This means that 20 orders per week have to be created and processed manual. It can be expected that the amount that
uses a VMOI or a similar delivery method will increase in the future, because of the ‘lean supply chain’ thinking (a VMOI fits into the lean philosophy).
3.2.1.2. Production order
Another issue is that most of the materials are ordered by their specific lead-time, excepting small ‘common parts’ (bolts and screws etc.). On planning date all the materials have to be in the
warehouse. In fact all material are ordered just-in-time. One item delivered late has consequences for the assemble process and the risk is that the process gets behind schedule. An associated
disadvantage is that suppliers have also no insight in upcoming orders and cannot act upon forecast, which could prevent late deliveries.
The production assistant (PA) is responsible for making physical assembly orders. He transforms the MPS (by the planner) to specific assembly orders for the shop floor. The target is to have the parts manufactured before the internal delivery date, defined by the integral planner with the use of the ERP system. If the process is running smoothly the function of the PA is more or less redundant, which is not the case at the moment. The supply of material lacks reliability and consistency as can be concluded from the CLIP and backlog of the purchase department (see Appendix G: CLIP and Backlog Purchasing). Even the own production at VDL ETG lacks the right on-time delivery (see Appendix H: CLIP and Backlog Parts).
3.2.1.3. Complexity in organisation
The process in Figure 11 is used to draw a swim lane for information flows (see Figure 12). Each lane belongs to a function within the hierarchical organization of VDL ETG. The initiating information is provided by the customer PMS and is translated by six functions before assembly starts. The shipment (next step after assembly) depends subsequently upon four steps. This indicates a certain dynamic complexity in the current situation.
The dynamic complexity is generated by two aspects, that VDL ETG is order-driven and the mainly functional organized organization. The last aspect needs clarification. The company has for each part in the process a different employee, divided by function. The planner is planning the orders; the order manager is accepting the order and so on. Too much complexity makes the process inflexible. This process shows that a small change in the forecast values, affects a chain of employees. And also a small adjustment by one of the employees affects all other functions, either positive or negative. And in the current state people are not sitting next to each other, which hinders clear communication.
3.2.1.4. Conclusion
The BaaN ERP system is not appropriate for the VMOI based agreement with PMS, because it adds extra (manual) steps and thus increases complexity. Lean theory focusses however on the reduction of complexity instead of adding complexity. While a VMOI agreement gives opportunity to reduce complexity. And another point of criticism is that in the current situation materials are ordered by lead-time, which gives risks for meeting the production schedule. Suppliers have also no insight in upcoming orders and cannot act upon a forecast. An unreliable delivery of purchased parts and produced parts is found. Another aspect is that complexity in the organisation is causing sensitivity to communication errors and other associated problems. It also makes the process inflexible to act upon changes.
3.2.2. Material logistics process
A lot of materials are needed for the production of a Miura component or a Fira system, as can be seen in Table 3 below. Most of the components are delivered and stored in the central warehouse at the home location (AQ). From there the right components are picked and transported to the external final assembly department (TX).
Table 3: Number of components in products
Assembly: Purchased: Make: Type of make component:
Miura c-arc geometry
113 9 Endstop cover FD/SO; handgrips;
geometry Miura c-arc
suspension
388 1 Brake lining
Fira X-Y 1281 4 Y-carriage
Fira rails 1550 54 Railparts; covers; spacers; brackets
Besides the materials picked by order also materials are delivered by a kanban system (e.g. bolts and screws). This is a common lean technique to reduce planning complexity between series of processes where continuous flow is not an option (because of distance, transport etc.) (Rother & Shook, 2003). Kanban creates a ‘pull’ in the value chain and it eliminates schedule problems. Kanban materials are delivered to TX and stored nearby the workplace. Empty bins are scanned and replenished by an external supplier. These materials are typical low cost and worth approximately one euro or less per piece.
3.2.2.1. Warehousing
The process that is executed in the warehouse can be found in Figure 13. The warehouse is a ‘closed type’ one where only authorized employees are able to access. About a year ago the warehouse was open for everyone, even visitors where able to enter the warehouse. This made it difficult to control the material flow and inventory, because regularly a discrepancy occurred between the real amount of materials in stock and the theoretical amount (provided by the BaaN ERP system).
Figure 13: Warehousing process (DSA)
The materials that enter the system are: supplied materials, materials returning from outsourcing, packages for employees and departments, and final products for further use in assemblies. In the warehouse some filter functions are present. In the scheme of Figure 13 three filters can be found; from left to right numbered 1,2 and 3. All filters have a different function and focus on different requirements:
- Filter 1: does the delivery match the delivery form (e.g. right package quantity; address)? - Filter 2: does the contents match the delivery form (e.g. right quantity of products)? - Filter 3: incoming goods inspection; does the product meet specifications (e.g. size)?
All incoming goods pass the first two filters. Filter 3 is optional for incoming goods; material from the internal production facility are certainly not passing filter 3. The quality aspect is further elaborated in
